An Approach of Image Processing for the Detection of Cercospora Fruit Spot and Bacterial Blight Disease on Pomegranate

India is one of the well-known countries in world, in the area of pharmacy specially food horticulture. India produces nearly 5.00 lakh tones/annum of pomegranate. Fruit gradation is one of the most vital parts in fruit horticulture. The project design presented by this paper is from same problematic area. In our project design we developed systems which classify diseases affecting pomegranates using K-means clustering and SVM techniques and routing algorithm. Now a days the disease Bacterial Blight which is caused by "Xanthomonas Axonopodis PV. Punicae" is growing rapidly day by day in pomegranate cultivation. This is fungal bacteria and caused by many parameters like environment, air, humidity, temperature. It causes heavy losses in production quality and quantity each year, especially in climates with rainfall and high temperature. Cercospora fruit spot is caused by the fungus and the full name of this fungal disease is “Pseudocercospora Angolensis”. Leaves of affected plants will produce circular spots with light brown to grayish centers. We are classifying the different pomegranate variety in accordance with their diseases. This paper deals with pomegranate grading and identification of disease system with judging parameters. The specialty of design is it creates a model which helps to decide appropriate criteria for healthy fruit. This project design is acts as advance system model in Indian horticulture for deciding ranges of mean, variance, entropy values by which the quality of fruit is decided. These parameters are judging parameters of our project design.